ISSN 2039-2117 (online)
ISSN 2039-9340 (print)
Mediterranean Journal of Social Sciences
Vol 5 No 20
September 2014
MCSER Publishing, Rome-Italy
Interactive Qualitative Analysis – A Novel Methodology for Qualitative Research
Dr Karen Bargate
Senior Lecturer: Managerial Accounting and Financial
Management, School of Accounting, Economics and Finance
University of KwaZulu-Natal; Durban; South Africa
bargate@ukzn.ac.za
Doi:10.5901/mjss.2014.v5n20p11
Abstract
This study investigates the use of Interactive Qualitative Analysis (IQA) (Northcutt & McCoy, 2004), as a methodology, to
develop an understanding of how Managerial Accounting and Financial Management students experienced learning in a writing
intensive tutorial programme. IQA is an innovative methodology providing a structured approach to conducting qualitative
research. Participants or constituents are actively engaged in data collection and analysis. Using thematic content analysis of
the data, they articulate their experiences of the phenomenon and identify emergent themes, or affinities and the relationship
between the affinities. The outcome of the IQA process is a Systems Influence Diagram, a visual representation of the
phenomenon, constructed through the lens of the constituents. What sets IQA apart from other forms of qualitative inquiry is
that it provides an audit trail of transparent and traceable procedures where the constituents, and not the researcher as expert,
do the analysis and interpretation of their data. The analysis of the data is as far as possible free from researcher bias as the
researcher is merely a facilitator of the process. The key value of this paper is that it offers a practical methodological approach
to using IQA in qualitative accounting education research, in particular, and business management education research, in
general.
Keywords: affinities; constituents; Interactive Qualitative Analysis; qualitative research; Systems Influence Diagram
1. Introduction
Qualitative research is an inquiry process aimed at understanding social or human problems based in a natural setting.
With qualitative research there are multiple perspectives of reality, which are subjective and open to researcher bias as
the researcher actively participates in the research process and analyses the data and in so doing builds an
understanding of a complex set of processes while reporting on the views of participants (Creswell 1994, p. 1,2). This
process raises issues related to lack of rigour, trustworthiness and reliability (Creswell, 2009; Denzin & Lincoln, 1998a,
1998b) which beset qualitative research. Interactive Qualitative Analysis (IQA) (Northcutt & McCoy, 2004) is an innovate
approach to qualitative research, which seeks to minimise the power relations and biases traditionally associated with
qualitative research (Paz Dennen, 2005; Tabane & Human-Vogel, 2010). With IQA, participants are actively engaged in
collecting and analysing the data. The outcome of the IQA process is a System Influence Diagram (SID), which is “a
visual representation of a phenomenon prepared according to rigorous and replicable rules for the purpose of achieving
complexity, simplicity, comprehensiveness and interpretability” (Northcutt & McCoy 2004, p. 41).
The value of this paper lies in offering a practical methodological approach to using IQA in a qualitative accounting
education study exploring Managerial Accounting and Financial Management (MAFM) students’ experiences of learning
in a writing intensive tutorial (WIT) programme. The detailed description of the IQA methodology process presented in
this study could be applied to other studies in areas of business management research.
The remainder of this paper is structured as follows: IQA as a qualitative research design method is considered
followed by a discussion of the ideology of IQA. Thereafter, the IQA process is described using MAFM students’
experiences of learning in a WIT programme as an illustrative example. The final section concludes the paper.
2. Interactive Qualitative Analysis
IQA (Northcutt & McCoy, 2004) is a structured approach to qualitative research design (du Preez & du Preez, 2012;
Mampane & Bouwer, 2011; Northcutt & McCoy, 2004). IQA uses focus groups to produce a systematic representation of
a phenomenon from participants’ experiences of the phenomenon being studied. IQA is based on the premise that those
11
ISSN 2039-2117 (online)
ISSN 2039-9340 (print)
Mediterranean Journal of Social Sciences
MCSER Publishing, Rome-Italy
Vol 5 No 20
September 2014
closest to the phenomenon being studied, the participants or constituents in IQA terminology, are best suited to construct
a graphic representation of the systems’ influences and outcomes. In the early stages of analysis, constituents’ voices are
privileged over that of the researcher. Constituents are defined as “a group of people who have a shared understanding
of the phenomenon” (Northcutt & McCoy 2004, p. 44), and are selected on the basis of their power over and distance
from (closeness to) the phenomenon under investigation. With traditional qualitative research, the researcher generates
the themes: however, with IQA, the constituents are responsible for the open coding of the data and generating themes
or affinities.
IQA as a research design is consistent with the principles of social constructivism because it “privileges the nature
of socially constructed meaning” (Northcutt & McCoy 2004, p. 4). It allows the group to construct categories of meaning,
affinities, and the role of the researcher is that of facilitator. The affinities provide the protocol for individual semistructured interviews where constituents’ experiences of the phenomenon can be further explored. An Interrelationship
Diagram (IRD) is developed portraying the cause and effect, or influence between affinities. A Systems Influence
Diagram (SID) is the final outcome. Northcutt and McCoy (2004, p.41) state: “The product of an IQA study is a visual
representation of a phenomenon prepared according to rigorous and replicable rules for the purpose of achieving
complexity, simplicity, comprehensiveness and interpretability.”
In the collection and analysis of data, constituents articulate their experiences of the phenomenon and develop
affinities in focus groups thus meaning is socially constructed. This process effectively reduces issues of trustworthiness,
dependability and conformability (Tabane, 2010). The role of the researcher is that of facilitator of the process, minimising
the researcher’s power and influence over constituents during data analysis. “The researcher’s role then moves from
designer to facilitator, teaching the group members the process and guiding them to generate and analyze their own data
with minimal external influence.” (Northcutt & McCoy 2004, p. 44). Consequently, the researcher’s biases and prejudices
are minimised in the process.
3. The Ideology of IQA
In this section, the ontological and epistemological assumptions as they inform the research method and design (Cohen,
Manion & Morrison 2007, p. 8 - 20) are described.
3.1 Ontological perspective
“IQA presumes that knowledge and power are largely dependent” (Northcutt & McCoy 2004, p. 16). The constituents are
selected because they hold the power and knowledge (which are inextricably linked) of the phenomenon being studied
through their membership of a particular group. In this study, constituents were selected due to their membership of the
WIT programme which provided them with authority to reflect on their experience of learning in that programme.
“IQA presumes that the observer and the observed are dependent or … interdependent” (Northcutt & McCoy 2004,
p. 16). IQA challenges the traditional assumptions of qualitative research which suggest that the role of participants is to
generate data, which only the researcher is qualified to analyse. With IQA, constituents generate and interpret their own
data while the researcher facilitates the process.
“The object of research in IQA is clearly reality in consciousness” (Northcutt & McCoy 2004, p. 16). The selection
of constituents is made from among those closest to the phenomenon, and in this study, students who participated in the
WIT programme. Data collection is undertaken in focus groups thus reality is socially constructed by members of the
group. Follow-up interviews are used to further probe individual meanings of the constructs. The central construct of this
study was learning, and the focus group format provided constituents with the opportunity to chronicle the processes by
which they learned MAFM in the WIT programme.
3.2 Epistemological perspective
“IQA insists that both deduction and induction are necessary to the investigation of meaning (Northcutt & McCoy 2004, p.
16). In IQA, categories of meaning or affinities are socially constructed by constituents in focus groups through induction.
Affinities are then defined and refined by the constituents (induction and deduction). In the final step, participants
deductively explore the relationship between constructs. The IQA process of coding corresponds with the traditional
classes of the analysis of coding – emergent, axial and theoretical (Northcutt & McCoy 2004, p. 16).
“IQA contends that decontextualized descriptions are useful and possible as long as they are backed up or
grounded … by highly contextualized ones” (Northcutt & McCoy 2004, p. 17). The researcher aids the reader by providing
12
ISSN 2039-2117 (online)
ISSN 2039-9340 (print)
Mediterranean Journal of Social Sciences
MCSER Publishing, Rome-Italy
Vol 5 No 20
September 2014
the context within which the research was conducted. Northcutt and McCoy (2004) refer to the Denzin and Lincoln
(1998a, p. 3) metaphor of the bricoleur as quilt maker. With IQA, the group, create their own interpretive quilt of meaning
or bricolage.
“IQA is clearly favorable to theory, both from the point of view of inducing theory and of testing it.” (Northcutt &
McCoy 2004, p. 17). The outcome of IQA is a mindmap of a group’s or an individual’s mental models of a particular
phenomenon. The relationship between constructs can then be theorised. The voices of those closest to the
phenomenon, constituents on the WIT programme, are privileged over that of the researcher.
4. The IQA Process
The first phase of the IQA entails the selection of constituents to participate in the study, focus group interviews, and
generation of a composite visual representation of the phenomenon. The second phase of data collection is semistructured interviews to further probe the constituents’ experiences of affinities developed in the focus groups and
subsequently theorise the relationships. Due to length constraints, this phase of the IQA process is not described in this
paper.
4.1 Identifying constituents
Constituents are selected according to the criteria of “distance and power” (Northcutt & McCoy 2004, p. 69) in relation to
the phenomenon being studied. Constituents for this study were a purposive sample of 15 MAFM students who
voluntarily participated in an 18-week WIT programme. They shared a direct and common experience of the
phenomenon, and in focus group sessions actively engaged in generating the data, coding it and eliciting affinities or
themes.
4.2 Focus group sessions
During the focus group phase of the IQA process, constituents’ experiences of the WIT programme were probed using
silent brainstorming for data generation. Constituents shared common perceptions of the WIT programme, however, each
constituent perceived the experience in different ways.
At the commencement of the focus groups, constituents were asked to relax, make themselves comfortable, close
their eyes, take a few deep breaths and clear their minds. They were then asked to silently reflect on their experiences of
learning in the WIT programme. In order to initiate reflection, an issue statement was provided by the facilitator. An issue
statement is “used to deconstruct and operationalise the research question” (Mampane & Bouwer 2011, p. 117). After a
brief discussion of the issue statement, constituents spent about 10 minutes silently reflecting on their experiences and
then wrote their reflections on Post-its. There was no limit to the number of Post-its each constituent could write,
however, there must be only one thought, experience or, word, per Post-it. Brainstorming is conducted in silence to
eliminate the influence of dominant members of the group. The facilitator is there to provide a safe environment to guide
the process and encourage constituents to write without censoring their thoughts, until they have exhausted their ideas
(Northcutt & McCoy 2004, p. 69). Once everyone has finished writing, Post-its are affixed randomly on a wall.
4.2.1 Affinity analysis
Once the brainstorming is complete, then the analysis of the data generated commences. In the clarification stage,
constituents are asked to begin by silently reading the Post-its which have been affixed to a wall. The facilitator then
reads each Post-it aloud to ensure that constituents understand what is written and to clarify if required.
4.2.2 Inductive coding
In the clustering stage, constituents arranged the Post-its in sets with common meanings. This continues until consensus
is reached with the placement of Post-its into affinity groupings yielding a collective view. Again this process should be
conducted silently to prevent dominant individuals or the facilitator monopolizing the process.
13
ISSN 2039-2117 (online)
ISSN 2039-9340 (print)
Mediterranean Journal of Social Sciences
MCSER Publishing, Rome-Italy
Vol 5 No 20
September 2014
4.2.3 Axial coding
Constituents then reviewed the Post-its under each grouping to ensure that they were under the correct themes. A Post-it
was placed at the top of each thematic grouping naming it. A limited amount of refining of Post-its was required to ensure
that all of the Post-its were correctly categorised into the relevant affinity. Affinities produced by each group were
aggregated and nine common affinities emerged. The nine affinities identified were: challenging; critique; enjoyable;
interactive; personal confidence, positive structure; study technique and test preparation; understanding; and written
tasks.
The IQA focus group process takes between three and four hours to complete (Lin & Tu, n.d.), which can be a
disadvantage of the IQA process if constituents do not have that length of time available (Lodewyckx, 2005). Once
affinities have been identified, a detailed affinity relationship table is constructed.
4.3 Detailed Affinity Relationship Table
An Affinity Relationship Table (ART) is completed by constituents to record an analysis of each pair of affinity
relationships. The relationship can be one of three,
• Understanding Ļ interaction (understanding influences interaction)
• Understanding Ĺ interaction (interaction influences understanding)
• Understanding < > interaction (no relationship between the affinities)
Further, constituents are asked to write a hypothesis “that reflects their experiences and that supports the cause
and effect relationship” (Northcutt & McCoy 2004, p. 152) between affinity pairs. This could be in the form of a short ‘ifthen’ statement. The responses are taken at face value as the true meaning of how constituents conceptualised the
affinity relationships (Human-Vogel 2006, p. 619).
The ART can be completed individually or in dyads or triads. In this study, seven constituents chose to complete it
individually and eight chose to do it with a friend, resulting in four dyads. The dyads took much longer to complete than
the individuals as they had to reach consensus on the direction of the arrows. The majority of the constituents took far
longer to complete the exercise than the facilitator had anticipated – more than 45 minutes. It is suggested that a
sufficient block of time is set aside to complete the exercise.
With IQA it is possible to analyse the ART at either a group composite level or an individual level to create the IRD.
In this study, relationships were analysed on a group level to determine the group’s composite understanding of the
phenomenon (Human-Vogel & Mahlangu, 2009). Pareto protocol is a statistical method that was used to determine the
optimal number of relationships to comprise the IRD. It is based on the fundamental principle that “A minority of the
relationships in any system will account for a majority of the variation within the system.” (Northcutt & McCoy 2004, p.
157). This optimum number of relationships will be at the point where power reaches a maximum. Using individual and
dyad ARTs, each relationship frequency is tallied, entered on a spreadsheet and the total number of votes for each
relationship calculated. A total of 344 votes were cast for all combinations of affinity pairs. The outcome of the process is
the frequency of each relationship in affinity pair order – see Annexure I. An appraisal of Annexure I indicates that
comparatively few of the possible 72 relationships account for most of the variance, consistent with the Pareto principle.
Figure 1 is an illustration of the variance accounted for by each succeeding relationship.
Figure 1: Cumulative percent – total relationships
As shown in Figure 2, power reaches a maximum (29.683) at 32 relationships which accounts for 74.128% of the
14
Mediterranean Journal of Social Sciences
ISSN 2039-2117 (online)
ISSN 2039-9340 (print)
Vol 5 No 20
September 2014
MCSER Publishing, Rome-Italy
variation in this system (Annexure I). Accordingly the first 32 affinity relationships will be included in the group IRD.
Figure 2: Cumulative percentage – total relationships
When deciding which relationships to include or exclude from the composite group IRD, the last two columns of the
Pareto table are pivotal in determining where to set the cut-off point as relationships are displayed in decreasing order of
frequency. Relationships 67 to 72 (Annexure I) are excluded as they failed to attract a single vote. However the decision
still needs to be made whether, in the composite IRD, to account for relationships such as those between 55 and 66
which attracted one or two votes. The elegance of the IQA is based on the trade-off between accounting “for maximum
variation in the system ... while minimizing the number of relationships in the interest of parsimony” (Northcutt & McCoy
2004, p. 160).
4.4 Creating a group composite: the Inter Relationship Diagram
The IRD is created from the first 32 affinity pair relationships (Annexure I), and this is the first step in rationalising the
system (Northcutt & McCoy 2004, p. 170). Each affinity relationship is mapped to create the composite IRD. The direction
of the arrow in each affinity pairing determines which affinity is influenced by which. Up arrows represent the row driving
the column and left arrows represent the column driving the row. For example, the first affinity pairing, 2 ĺ 6 signifies
that affinity 2 (understanding), cause, is influencing affinity 6 (enjoyment), effect. The IRD works on a similar principle to
double-entry booking as every affinity will have ‘two entries’ in the tabular IRD and the ‘outs’ and ‘ins’ need to balance
with the number of affinity relationship pairs (32). Thus affinity 2 will have Ĺ (out) into affinity 6 and the balancing entry will
be ĸ (in) to affinity 2 from affinity 6 (Table 1). Delta (¨) is the difference between the ‘outs’ and ‘ins’ for each affinity.
Table 1: Composite focus group IRD - sorted in descending order
*
1
2
4
3
9
5
6
7
8
1
Ĺ
Ĺ
Ĺ
ĺ
Ĺ
Ĺ
Ĺ
Ĺ
2
ĺ
ĺ
Ĺ
Ĺ
Ĺ
Ĺ
Ĺ
Ĺ
3
ĺ
ĺ
Ĺ
Ĺ
Ĺ
Ĺ
4
ĺ
Ĺ
ĺ
Ĺ
Ĺ
Ĺ
Ĺ
Ĺ
5
ĺ
ĺ
ĺ
ĺ
ĺ
Ĺ
Ĺ
Ĺ
6
ĺ
ĺ
ĺ
ĺ
7
ĺ
ĺ
ĺ
ĺ
ĺ
ĺ
ĺ
Ĺ
Ĺ
Ĺ
8
ĺ
ĺ
ĺ
Ĺ
ĺ
ĺ
ĺ
9
Ĺ
ĺ
ĺ
Ĺ
ĺ
outĺ
7
6
6
4
2
3
2
1
1
inĹ
1
2
2
2
3
5
5
6
6
¨
6
4
4
2
-1
-2
-3
-5
-5
*Affinities: 1 – positive structure; 2 – understanding; 3 – written tasks; 4 – challenging; 5 – study technique and
test preparation; 6 – enjoyment; 7 – personal confidence; 8 – interaction; 9 – critique
The IRD provided the data needed to determine which affinities were drivers or outcomes. Affinities with positive deltas
(1, 2, 4, 3) are drivers or causes and affinities with negative deltas (9, 5, 6, 7, 8) are outcomes or effects. Positive
structure (1) is the primary driver of the system and personal confidence (7) and interaction (8) are primary outcomes.
This classification is indicative of a strong cause or effect relationship between relevant affinities. Understanding (2),
challenging (4) and written tasks (3) are secondary drivers and critique (9), study technique and test preparation (5) and
15
ISSN 2039-2117 (online)
ISSN 2039-9340 (print)
Mediterranean Journal of Social Sciences
MCSER Publishing, Rome-Italy
Vol 5 No 20
September 2014
enjoyment (6) are secondary outcomes.
4.5 Focus group Systems Influence Diagram (SID)
4.5.1 Cluttered SID
The aggregated focus group data is utilised in drawing the SID. The SID is a visual representation of all relationships of
the entire system (Northcutt & McCoy 2004, p. 174). When drawing the SID primary drivers are placed on the extreme
left-hand side and primary outcomes on the extreme right-hand side. Secondary outcomes and drivers are placed
between primary drivers and outcomes with drivers placed on the left and outcomes on the right. For every relationship in
the IRD (Table 1) an arrow is drawn between the two affinities indicating the direction of cause and effect the product of
which is the cluttered SID, see Figure 3. The cluttered SID has limited explanatory value as it is too complex for
meaningful analysis. For the SID to have relevance it is a precondition that it be uncluttered by removing redundant links.
Figure 3: Cluttered SID
4.5.2 Uncluttered SID
Once the relationships are examined all redundant links are removed to simplify the diagram, resulting in an uncluttered
SID. In the cluttered SID (Figure 3), 1 ĺ 3 would be considered a redundant link because 1 ĺ 2 and 2 ĺ 3, hence the
link 1 ĺ 3 can be removed making the system simpler and one that has optimum explanatory power (Northcutt &
McCoy, 2004, p. 177). The process of removing redundant links continued until all had been removed and the resultant
uncluttered SID represents MAFM students’ experiences of learning in a WIT programme. Figure 4 shows the uncluttered
SID.
Figure 4: Uncluttered SID
4.6 A tour through the system
Looking at the uncluttered SID represented in Figure 4, the following interpretation can be offered. Learning experiences
of MAFM students in a WIT programme are driven by the structure of the programme and this influences students’
understanding and the challenging nature of the tasks completed. Improved understanding influences the written tasks,
16
ISSN 2039-2117 (online)
ISSN 2039-9340 (print)
Mediterranean Journal of Social Sciences
MCSER Publishing, Rome-Italy
Vol 5 No 20
September 2014
which in turn influences the challenging nature of the programme and this influences understanding of MAFM. These
three elements form a feedback loop. Written tasks influence enjoyment and the challenging nature influences study
technique and test preparation. The enjoyment affinity influences personal confidence which influences interaction and
this influences critique, which influences studying technique and test preparation. Another feedback loop is formed
between affinities 6, 7, 8, 9 and 5. The outcome of the system is representative of the interactive nature of the WIT
programme.
4.7 Feedback loops and zooming
Within the system two feedback loops were identified:
ƒ understanding, written tasks challenging, enjoyment; and
personal confidence, interaction, critique and study technique and test preparation.
ƒ
Northcutt and McCoy (2004, p. 335) state that a feedback loop consists of at “least three affinities, each influencing
the other directly or indirectly”. Feedback loops can be renamed by reviewing the components of each subsystem. The
process is referred to as “zooming” (Northcutt & McCoy 2004, p. 335). The substitute name for subsystems is generated
by reviewing the axial coding and descriptions together with the placements of the feedback loops within the overall
system. The defined components of the first subsystem (2, 3, 4) suggest intellectually stimulating. The defined
components of the second subsystem (6, 7, 8, 9, 5) suggest learning is fun. These new “superaffinities” replace the
feedback loops via substitution in a new view that is zoomed out (Northcutt & McCoy 2004, p. 335) (see Figure 5).
Figure 5: WIT learning experience telephoto view SID
The new system is identical to the first (Figure 4) except that the seven affinities from the two feedback loops have been
collapsed or zoomed out into more general terms – ‘intellectually stimulating’ and ‘learning is fun’. This telephoto view SID
cannot be zoomed any further and the result is an elegant linear system with no branching.
5. Conclusion
This paper discusses IQA as a research method, with application to a WIT programme. In this study, affinities were
identified by constituents and presented in the ART from which relationships between affinities were described in the IRD.
The culmination of the process (for this study) is the SID which is a visual representation of the system. So far as the
researcher has determined, this is the first time IQA has been used in accounting education research.
The value in using IQA as a research design is that it scales back the power relations between researcher and
participants. IQA ensures that the voice of the participants is valued and supplements the voice of the researcher. IQA is
a complex procedure and if the entire process had been adhered to data collection would have extended beyond the
duration of the WIT programme. IQA also imposes time demands on participant subjects. However, using the principles
of IQA, the context determines how far the theory can be applied.
References
Cohen. L., Manion L. & Morrison K. (2007). Research methods in education. Routledge: London
Creswell, J. W. (1994). Research design qualitative and quantitative approaches. Thousand Oaks: SAGE.
Creswell, J. W. (2009). Research design qualitative, quantitative and mixed methods approaches. Thousand Oaks: SAGE.
Denzin, N. K. & Lincoln, Y. S. (eds.) (1998a). Collecting and interpreting qualitative materials. Thousand Oaks: SAGE.
Denzin, N. K. and Lincoln, Y. S. (eds.) (1998b). The landscape of qualitative research theories and issues. Thousand Oaks: SAGE.
du Preez, H. & du Preez, C. (2012). Taxation students’ perceptions of open-book assessment prior to the qualifying examination of
South African Chartered Accountants. South African Journal of Accounting Research, 26(1), 119-142.
Human-Vogel, S. (2006). Students’ mental modes of positive mood and self-regulation in learning. Psychological Society of South Africa,
36(3), 613-633.
Human-Vogel, S. & Mahlangu, P. P. (2009). Commitment in academic contexts: first year education students’ beliefs about the aspects
of self, the lecturer and instruction. South African Journal of Higher Education, 23(2), 309-328.
17
Mediterranean Journal of Social Sciences
ISSN 2039-2117 (online)
ISSN 2039-9340 (print)
MCSER Publishing, Rome-Italy
Vol 5 No 20
September 2014
Lin, C.-Y. & Tu, C.-C. (n.d.). Combined IQA approach with a case study for information system requirements. [Online] Available:
http://140.130.135.23:8080/dspace/bitstream/TTCIR/405/1/PICMET2010-%E6%9E%97%E7%B4%94%E9%9B%85.pdf.
Lodewyckx, D. P. G. (2005). An Interactive Qualitative Analysis of educational psychology students' self-efficacy beliefs in career
counselling. [Online] Available: http://upetd.up.ac.za/thesis/available/etd-12202006-132015/unrestricted/00dissertation.pdf.
Mampane, R. & Bouwer, C. (2011). The influence of township schools on the resillience of their learners. South African Journal of
Education, 31(1), 114-126.
Northcutt, N. & McCoy, D. (2004). Interactive Qualitative Analysis: a systems method for qualitative research. London: SAGE.
Paz Dennen, V. (2005). Book review: Interactive Qualitative Analysis: a systems method for qualitiative analysis, N. Northcutt, D. McCoy,
SAGE (2004). Evaluation and Program Planning, 28, 315-316.
Tabane, R. J. (2010). Integration and learners' feelings of belonging in a desegregated former House of Delegates school. [Online]
Available Doctor of Philosophy. University of Pretoria, http://upetd.up.ac.za/thesis/available/etd-05012010-163911/.
Tabane, R. J. & Human-Vogel, S. (2010). Sense of belonging and social cohension in a desegregated former House of Delegates
school. South African Journal of Education, 30(3), 495-504.
Annexure I: Affinities in descending order of frequency with Pareto protocol and power
No
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
Affinity pair
relationship
2ĺ6
1ĺ8
2ĺ7
2ĺ3
1ĺ2
4ĺ8
4ĺ5
3ĺ7
3ĺ6
2ĸ4
1ĺ6
1ĺ5
1ĺ4
1ĺ3
7ĺ8
4ĺ7
3ĺ5
3ĺ4
6ĺ8
4ĺ9
4ĺ6
2ĺ9
2ĺ8
1ĺ7
8ĺ9
6ĺ7
5ĸ9
5ĺ8
5ĺ7
5ĺ6
1ĸ9
2ĺ5
2ĸ5
6ĸ8
3ĺ9
7ĸ9
7ĸ8
7ĺ9
6ĸ9
5ĸ8
Frequency sorted
(descending)
11
11
10
10
10
9
9
9
9
9
9
9
9
9
8
8
8
8
7
7
7
7
7
7
6
6
6
6
6
6
6
6
4
4
4
4
3
3
3
3
Cumulative
frequency
11
22
32
42
52
61
70
79
88
97
106
115
124
133
141
149
157
165
172
179
186
193
200
207
213
219
225
231
237
243
249
255
259
263
267
271
274
277
280
283
18
Cumulative percent
(relation)
1.389
2.778
4.167
5.556
6.944
8.333
9.722
11.111
12.500
13.889
15.278
16.667
18.056
19.444
20.833
22.222
23.611
25.000
26.389
27.778
29.167
30.556
31.944
33.333
34.722
36.111
37.500
38.889
40.278
41.667
43.056
44.444
45.833
47.222
48.611
50.000
51.389
52.778
54.167
55.556
Cumulative percent
(frequency)
3.198
6.395
9.302
12.209
15.116
17.733
20.349
22.965
25.581
28.198
30.814
33.430
36.047
38.663
40.988
43.314
45.640
47.965
50.000
52.035
54.070
56.105
58.140
60.174
61.919
63.663
65.407
67.151
68.895
70.640
72.384
74.128
75.291
76.453
77.616
78.779
79.651
80.523
81.395
82.267
Power
1.809
3.618
5.136
6.654
8.172
9.399
10.627
11.854
13.081
14.309
15.536
16.764
17.991
19.218
20.155
21.092
22.028
22.965
23.611
24.257
24.903
25.549
26.195
26.841
27.196
27.552
27.907
28.262
28.618
28.973
29.328
29.683
29.457
29.231
29.005
28.779
28.262
27.745
27.229
26.712
Mediterranean Journal of Social Sciences
ISSN 2039-2117 (online)
ISSN 2039-9340 (print)
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
5ĸ7
5ĸ6
5ĺ9
4ĸ9
4ĸ5
3ĸ9
3ĸ7
3ĸ5
3ĺ8
2ĸ8
2ĺ4
1ĸ5
1ĺ9
8ĸ9
6ĸ7
4ĸ6
3ĸ4
2ĺ3
1ĺ2
2ĸ7
6ĺ9
4ĸ8
3ĸ8
2ĸ9
1ĸ7
1ĸ4
4ĸ7
3ĸ6
2ĸ6
1ĸ8
1ĸ6
1ĸ3
Vol 5 No 20
September 2014
MCSER Publishing, Rome-Italy
3
3
3
3
3
3
3
3
3
3
3
3
3
3
2
2
2
2
2
2
2
1
1
1
1
1
0
0
0
0
0
0
286
289
292
295
298
301
304
307
310
313
316
319
322
325
327
329
331
333
335
337
339
340
341
342
343
344
344
344
344
344
344
344
56.944
58.333
59.722
61.111
62.500
63.889
65.278
66.667
68.056
69.444
70.833
72.222
73.611
75.000
76.389
77.778
79.167
80.556
81.944
83.333
84.722
86.111
87.500
88.889
90.278
91.667
93.056
94.444
95.833
97.222
98.611
100.000
19
83.140
84.012
84.884
85.756
86.628
87.500
88.372
89.244
90.116
90.988
91.860
92.733
93.605
94.477
95.058
95.640
96.221
96.802
97.384
97.965
98.547
98.837
99.128
99.419
99.709
100.000
100.000
100.000
100.000
100.000
100.000
100.000
26.195
25.678
25.161
24.645
24.128
23.611
23.094
22.578
22.061
21.544
21.027
20.510
19.994
19.477
18.669
17.862
17.054
16.247
15.439
14.632
13.824
12.726
11.628
10.530
9.432
8.333
6.944
5.556
4.167
2.778
1.389
0.000